Method and apparatus with measuring of three-dimensional position using radar sensor

ABSTRACT

A method with three-dimensional (3D) position measuring using a radio detection and ranging (radar) sensor includes: transmitting, through the radar sensor, a transmission signal of which a carrier frequency varies over time; obtaining, through the radar sensor, a reflected signal from the transmission signal being reflected by an object; obtaining a beat frequency signal indicating a frequency difference between the transmission signal and the reflected signal; and estimating 3D position information of the object based on groups of sample data of different frequency bands extracted from the beat frequency signal.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. § 119(a) of KoreanPatent Application No. 10-2019-0148329 filed on Nov. 19, 2019, in theKorean Intellectual Property Office, the entire disclosure of which isincorporated herein by reference for all purposes.

BACKGROUND 1. Field

The following description relates to three-dimensional (3D) positionmeasurement using a radio detection and ranging (radar) sensor.

2. Description of Related Art

Recently released vehicles are commonly equipped with an active safetysystem to protect drivers and reduce the risk of accidents. The activesafety system may require sensors configured to recognize an externalenvironment. A radio detection and ranging (radar) sensor is widely usedamong such sensors. is the radar sensor may be used because the radarsensor may be more robust against effects of weather or other externalenvironmental conditions, in comparison to other sensors configured torecognize an external environment.

A signal of a frequency-modulated continuous-wave (FMCW) is frequentlyused for the radar sensor, because such a signal is easily produced andhas relatively high performance in detecting vehicle information. Aradar sensor using such an FMCW signal may transmit a chirp signal ofwhich a frequency is linearly modulated, and a corresponding radarsystem may analyze a signal reflected from a target and estimate adistance to the target and a velocity of the target.

SUMMARY

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

In one general aspect, a method with three-dimensional (3D) positionmeasuring using a radio detection and ranging (radar) sensor includes:transmitting, through the radar sensor, a transmission signal of which acarrier frequency varies over time; obtaining, through the radar sensor,a reflected signal from the transmission signal being reflected by anobject; obtaining a beat frequency signal indicating a frequencydifference between the transmission signal and the reflected signal; andestimating 3D position information of the object based on groups ofsample data of different frequency bands extracted from the beatfrequency signal.

The estimating of the 3D position information of the object may include:extracting a plurality of groups of sample data from the beat frequencysignal corresponding to a chirp signal, the plurality of groups ofsample data including the groups of sample data of the differentfrequency bands; and estimating a distance and an elevation angle withrespect to a position of the object based on the groups of sample dataof the different frequency bands.

The estimating of the distance and the elevation angle may include:estimating the distance and the elevation angle with respect to theposition of the object by applying a time-frequency analysis method tothe groups of sample data of the different frequency bands.

The estimating of the distance and the elevation angle may include:calculating the distance and the elevation angle simultaneously throughthe time-frequency analysis method.

The time-frequency analysis method may be a short-time Fourier transform(STFT) or a wavelet transform (WT).

The estimating of the 3D position information of the object may include:estimating an elevation angle with respect to a position of the objectusing a change of a center direction of the transmission signal for eachfrequency band among frequency bands of transmitting antennas includedin the radar sensor.

The transmitting antennas may be arranged in a horizontal direction inthe radar sensor.

The 3D position information may include a distance, an azimuth, and anelevation angle with respect to a position of the object.

The estimating of the 3D position information of the object may include:estimating an azimuth with respect to a position of the object based onbeat frequency signals respectively corresponding to receiving antennasof the radar sensor.

The estimating of the azimuth may include estimating the azimuth throughdigital beamforming for estimating a direction in which the reflectedsignal is received based on a difference occurring among the beatfrequency signals.

The carrier frequency may be modulated based on a frequency modulationmodel that uses linear frequency modulation.

In another general aspect, a non-transitory computer-readable storagemedium stores instructions that, when executed by a processor, cause theprocessor to perform the method described above.

In another general aspect, an apparatus with three-dimensional (3D)position measuring includes: a radio detection and ranging (radar)sensor configured to transmit a transmission signal of which a carrierfrequency varies over time, and obtain a reflected signal from thetransmission signal being reflected by an object; and a processorconfigured to obtain a beat frequency signal indicating a frequencydifference between the transmission signal and the reflected signal, andestimate 3D position information of the object based on groups of sampledata of different frequency bands extracted from the beat frequencysignal.

The processor may be further configured to: extract a plurality ofgroups of sample data from the beat frequency signal corresponding to achirp signal, the plurality of groups of sample data including thegroups of sample data of the different frequency bands; and estimate adistance and an elevation angle with respect to a position of the objectbased on the groups of sample data of the different frequency bands.

The processor may be further configured to: estimate the distance andthe elevation angle with respect to the position of the object byapplying a time-frequency analysis method to the groups of sample dataof the different frequency bands.

The time-frequency analysis method may be a short-time Fourier transform(STFT) or a wavelet transform (WT).

The processor may be further configured to: estimate an elevation anglewith respect to a position of the object using a change of a centerdirection of the transmission signal for each frequency band amongfrequency bands of transmitting antennas included in the radar sensor.

The processor may be further configured to: estimate an azimuth withrespect to a position of the object based on beat frequency signalsrespectively corresponding to receiving antennas of the radar sensor.

The processor may be further configured to: estimate the azimuth throughdigital beamforming for estimating a direction in which the reflectedsignal is received based on a difference occurring among the beatfrequency signals.

In another general aspect, an apparatus with three-dimensional (3D)position measuring includes a radio detection and ranging (radar) sensorand a processor. The radar sensor is configured to: transmit atransmission signal of which a carrier frequency varies over time, usinga plurality of transmission antennas corresponding to respectivefrequency bands of the transmission signal; and obtain a reflectedsignal from the transmission signal being reflected by an object. Theprocessor is configured to: obtain beat frequency signals respectivelycorresponding to receiving antennas of the radar sensor and indicating afrequency difference between the transmission signal and the reflectedsignal; and estimate 3D position information of the object based ongroups of sample data of different frequency bands extracted from thebeat frequency signals.

The 3D position information may include a distance and an elevation of aposition of the object relative to a position of the apparatus.

The processor may be further configured to estimate the 3D positioninformation by estimating an elevation angle with respect to a positionof the object based on a change of a center direction of thetransmission signal for each of the respective frequency bands of thetransmission signal.

The processor may be further configured to estimate the 3D positioninformation by estimating a distance and an elevation angle with respectto a position of the object by applying a time-frequency analysis methodto the groups of sample data of the different frequency bands.

Other features and aspects will be apparent from the following detaileddescription, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1a and 1b are diagrams illustrating an example of measuring athree-dimensional (3D) position using a radio detection and ranging(radar) sensor.

FIG. 2 is a diagram illustrating an example of a change of a centerdirection of a transmission signal in a vertical direction according toa frequency band.

FIG. 3 is a diagram illustrating an example of a configuration of a 3Dposition measuring apparatus.

FIG. 4 is a diagram illustrating an example of a 3D position measuringapparatus.

FIG. 5 is a diagram illustrating an example of an arrangement ofantennas of a radar sensor.

FIG. 6 is a diagram illustrating an example of a receiving antenna arrayof a radar sensor.

FIG. 7 is a diagram illustrating an example of estimating distanceinformation and elevation angle information from a reflected signal.

FIGS. 8 and 9 are flowcharts illustrating an example of a 3D positionmeasuring method using a radar sensor.

FIG. 10 is a diagram illustrating an example of a computing apparatus.

Throughout the drawings and the detailed description, the same referencenumerals refer to the same elements. The drawings may not be to scale,and the relative size, proportions, and depiction of elements in thedrawings may be exaggerated for clarity, illustration, and convenience.

DETAILED DESCRIPTION

The following detailed description is provided to assist the reader ingaining a comprehensive understanding of the methods, apparatuses,and/or systems described herein. However, various changes,modifications, and equivalents of the methods, apparatuses, and/orsystems described herein will be apparent after an understanding of thedisclosure of this application. For example, the sequences of operationsdescribed herein are merely examples, and are not limited to those setforth herein, but may be changed as will be apparent after anunderstanding of the disclosure of this application, with the exceptionof operations necessarily occurring in a certain order. Also,descriptions of features that are known may be omitted for increasedclarity and conciseness.

The features described herein may be embodied in different forms, andare not to be construed as being limited to the examples describedherein. Rather, the examples described herein have been provided merelyto illustrate some of the many possible ways of implementing themethods, apparatuses, and/or systems described herein that will beapparent after an understanding of the disclosure of this application.

Herein, it is noted that use of the term “may” with respect to anexample or embodiment, e.g., as to what an example or embodiment mayinclude or implement, means that at least one example or embodimentexists in which such a feature is included or implemented while allexamples and embodiments are not limited thereto.

Throughout the specification, when an element, such as a layer, region,or substrate, is described as being “on,” “connected to,” or “coupledto” another element, it may be directly “on,” “connected to,” or“coupled to” the other element, or there may be one or more otherelements intervening therebetween. In contrast, when an element isdescribed as being “directly on,” “directly connected to,” or “directlycoupled to” another element, there can be no other elements interveningtherebetween. As used herein, the term “and/or” includes any one and anycombination of any two or more of the associated listed items.

Although terms such as “first,” “second,” and “third” may be used hereinto describe various members, components, regions, layers, or sections,these members, components, regions, layers, or sections are not to belimited by these terms. Rather, these terms are only used to distinguishone member, component, region, layer, or section from another member,component, region, layer, or section. Thus, a first member, component,region, layer, or section referred to in examples described herein mayalso be referred to as a second member, component, region, layer, orsection without departing from the teachings of the examples.

The terminology used herein is for describing various examples only andis not to be used to limit the disclosure. The articles “a,” “an,” and“the” are intended to include the plural forms as well, unless thecontext clearly indicates otherwise. The terms “comprises,” “includes,”and “has” specify the presence of stated features, numbers, operations,members, elements, and/or combinations thereof, but do not preclude thepresence or addition of one or more other features, numbers, operations,members, elements, and/or combinations thereof.

The features of the examples described herein may be combined in variousways as will be apparent after an understanding of the disclosure ofthis application. Further, although the examples described herein have avariety of configurations, other configurations are possible as will beapparent after an understanding of the disclosure of this application.

FIGS. 1a and 1b are diagrams illustrating an example of measuring athree-dimensional (3D) position using a radio detection and ranging(radar) sensor.

Referring to FIG. 1a , an apparatus 100 for measuring a 3D position(hereinafter “3D position measuring apparatus”), may measure, using aradar sensor 110, a 3D position of one or more objects, for example, anobject 120 and an object 130, that are present adjacent to the 3Dposition measuring apparatus 100. According to an example, the 3Dposition measuring apparatus 100 may be applied to an advanced driverassistance system (ADAS) that provides a driver safety and conveniencethrough various sensors located inside or outside a vehicle, arecognition system for facial recognition or gesture recognition, asurveillance/security system, and the like. Hereinafter, an example ofestimating a 3D position of an object present around the 3D positionmeasuring apparatus 100 by the 3D position measuring apparatus 100,wherein the 3D position measuring apparatus 100 is disposed in avehicle, will be mainly described. However, the scope of this disclosureis not limited to the example described herein. The 3D positionmeasuring apparatus 100 may also be used for various other applicationsthat utilize 3D position information of an object.

The radar sensor 110 may be disposed inside or outside the 3D positionmeasuring apparatus 100, and may radiate a transmission signal forestimating a position of an object, for example, the objects 120 and130, through one or more transmitting antennas. In an example, the radarsensor 110 may be a frequency-modulated continuous-wave (FMCW) radarsensor that has a plurality of transmitting antennas and is configuredto radiate, through the transmitting antennas, an FMCW transmissionsignal of which a carrier frequency varies over time. The transmissionsignal radiated from the radar sensor 110 may be reflected by the one ormore objects, for example, the objects 120 and 130, and one or morereflected signals may be obtained from the transmission signal beingreflected by the one or more objects. The reflected signal(s) may beobtained through one or more receiving antennas included in the radarsensor 110. In an example, the radar sensor 110 may have a plurality ofreceiving antennas.

The 3D position measuring apparatus 100 may then estimate the 3Dposition of the one or more objects, for example, the objects 120 and130, by analyzing the reflected signal(s) obtained through the receivingantennas. In an example, the 3D position measuring apparatus 100 mayestimate a distance from the 3D position measuring apparatus 100 to theobject present nearby, and an azimuth corresponding to a position of theobject in a horizontal direction or a horizontal angle. In addition, the3D position measuring apparatus 100 may estimate an elevation anglecorresponding to a position of the object 130 in a vertical direction ora vertical angle, as illustrated in FIG. 1b . As described above, the 3Dposition measuring apparatus 100 may estimate 3D position informationincluding a distance, an azimuth, and an elevation angle with respect toa position of the object, for example, the objects 120 and 130.According to an example, the 3D position measuring apparatus 100 mayestimate a 3D position of an object based on data obtained by othersensors, for example, an image sensor and the like, in addition to areflected signal obtained using the radar sensor 110. The reflectedsignal described herein may also be referred to as a received signal.

Hereinafter, a way by which the 3D position measuring apparatus 100measures a 3D position of an object using the radar sensor 110 will bedescribed in greater detail.

FIG. 2 is a diagram illustrating an example of a change of a centerdirection of a transmission signal in a vertical direction according toa frequency band.

Referring to FIG. 2, a radar sensor 200 used by a 3D position measuringapparatus may transmit an FMCW transmission signal of which a frequencyvaries over time. A center direction of the transmission signal of theradar sensor 200 may vary in a vertical direction based on a frequencyband. The vertical direction may correspond to a direction perpendicularto a horizontal plane. For example, as a carrier frequency of thetransmission signal to be transmitted from the radar sensor 200increases, the center direction of the transmission signal may alsogradually rise in the vertical direction. This may be attributed to atransmission characteristic based on an arrangement and a structure oftransmitting antennas of the radar sensor 200. In the example of FIG. 2,when a carrier frequency gradually increases from f1 to f4, a centerdirection of a transmission signal of the carrier frequency f1 may facetoward a bottom and the center direction of the transmission signal ofthe carrier frequency f4 may face toward a top. The 3D positionmeasuring apparatus may estimate an elevation angle associated with aposition of an object in a vertical direction using the characteristicof the radar sensor 200 described above.

FIG. 3 is a diagram illustrating an example of a configuration of a 3Dposition measuring apparatus.

Referring to FIG. 3, a 3D position measuring apparatus 300 includes, forexample, a radar sensor 310 and a processor 320.

The radar sensor 310 may sense radar data. For example, the radar sensor310 may transmit a transmission signal of which a carrier frequencyvaries over time through one or more transmitting antennas, and mayobtain a reflected signal from the transmission signal being reflectedby an object through one or more receiving antennas. The transmissionsignal may be an FMCW signal that is generated based on a frequencymodulation model, and the FMCW signal may be radiated externally to betransmitted outside the radar sensor 310 through the transmittingantennas. The radiated FMCW signal may be reflected from the object, andthe reflected signal which is obtained from the FMCW signal beingreflected by the object may be received by the receiving antennas andform the radar data. In an example, the radar sensor 310 may include thetransmitting antennas respectively corresponding to a plurality oftransmission channels (indicated by Tx (see FIG. 4)) and the receivingantennas respectively corresponding to a plurality of reception channels(indicated by Rx (see FIG. 4)).

The processor 320 may control operations and functions of the 3Dposition measuring apparatus 300. The processor 320 may set a detectionarea and a detection resolution of the 3D position measuring apparatus300, and adjust a characteristic of the transmission signal based on theset detection area and the set detection resolution. For example, theprocessor 320 may adjust a characteristic of the carrier frequency ofthe transmission signal, for example, a frequency range, a slope, afrequency change time, and the like, and/or adjust a characteristic ofan intensity of the transmission signal. The detection area may be setbased on a detection range and a detection angle. The detectionresolution may be set based on a detection unit of a position of anobject, for example, 1 meter (m) and 50 centimeters (cm).

The processor 320 may estimate 3D position information and/or a velocityof the object by analyzing the radar data sensed through the radarsensor 310. The 3D position information may be information thatspecifies a 3D position of the object and may include, for example, adistance, an azimuth, and an elevation angle with respect to a positionof the object. Hereinafter, an example of measuring the distance, theazimuth, and the elevation angle as the 3D position information will bedescribed in greater detail. However, the 3D position information of theobject may also be represented by an orthogonal coordinate system or apolar coordinate system, and there is no limit to a method ofrepresenting such information.

In an example, the processor 320 may obtain a beat frequency signalindicating a frequency difference between the transmission signal andthe reflected signal based on the transmission signal and the reflectedsignal. The beat frequency signal may also be referred to as anintermediate frequency signal.

The processor 320 may extract groups of sample data of differentfrequency bands from the beat frequency signal, and estimate the 3Dposition information of the object based on the extracted groups ofsample data. In an example, the processor 320 may extract the groups ofsample data by sampling a beat frequency signal corresponding to a chirpsignal at a plurality of sampling points. The chirp signal may refer toa signal of which a frequency varies over time. The processor 320 maysample the beat frequency signal at the sample points, and obtain thegroups of sample data by performing analog-to-digital conversion thatconverts a sampled analog signal value to a corresponding digitalsignal.

The processor 320 may estimate the distance and the elevation angle withrespect to the position of the object based on the groups of sample dataof the different frequency bands that are included in the obtainedgroups of sample data. As described above with reference to FIG. 2, theprocessor 320 may estimate the elevation angle with respect to theposition of the object using a characteristic of a change of a centerdirection of the transmission signal for each frequency band. In anexample, the processor 320 may estimate the distance and the elevationangle with respect to the position of the object by applying atime-frequency analysis method to the groups of sample data of thedifferent frequency bands. The time-frequency analysis method may be ashort-time Fourier transform (STFT) or a wavelet transform (WT).According to an example, the processor 320 may determine the distancewith respect to the position of the object using a high-resolution rangeprofile (HRRP). Herein, the terms “distance” and “range” may be usedinterchangeably. Hereinafter, an example of estimating a distance and/oran elevation angle with respect to a position of an object based on abeat frequency signal will be described in greater detail with referenceto FIGS. 4 through 7.

The processor 320 may estimate the azimuth with respect to the positionof the object based on beat frequency signals respectively correspondingto the receiving antennas of the radar sensor 310. In an example, theprocessor 320 may estimate the azimuth with respect to the position ofthe object using, for example, digital beamforming (DBF), estimation ofsignal parameters via rotational invariance technique (ESPRIT), multiplesignal classification (MUSIC), minimum variance distortionless response(MVDR), or a Bartlett's method. For example, the processor 320 maydesirably estimate an azimuth corresponding to a position of the objectin a horizontal direction through DBF. An example of estimating such anazimuth will be described in more detail hereinafter.

In an example, groups of sample data of a beat frequency signal may berepresented by Equation 1.

Y=[Y(1),Y(2), . . . ,Y(i), . . . ,Y(N−1),Y(N)]  [Equation 1]

In Equation 1, i is a time index, which is a natural number greater thanor equal to 1 and less than or equal to N. N is the number of groups ofsample data sampled from the beat frequency signal, which is a naturalnumber greater than or equal to 1. Y is data obtained by converting ananalog value of the beat frequency signal to a digital value. Forexample, when a receiving antenna array included in the radar sensor 310includes M receiving antennas, sample data Y(i) at an ith sampling pointcorresponding to a time index i may be represented by Equation 2.

Y(i)=[s ₁(i),s ₂(i), . . . ,s _(m)(i), . . . ,s _(M−1)(i),s_(M)(i)]^(T)  [Equation 2]

In Equation 2, s_(m)(i) is a sampled value from ith sample data bysampling an intensity of a reflected signal received by an mth receivingantenna among the M receiving antennas. M is a natural number greaterthan or equal to 2, and m is a natural number greater than or equal to 1and less than or equal to M. A normalization model may then be appliedto the sample data Y(i). The normalization model may be represented byEquation 3.

A _(pNorm) ={A _(pNorm,1) , . . . ,A _(pNorm,i) , . . . ,A_(pNorm,N)}  [Equation 3]

In Equation 3, A_(pNorm,i) is an ith normalization matrix to be appliedto a value of the ith sample data among groups of sample data. The ithnormalization matrix may be represented by Equation 4.

A _(pNorm,i) =A _(f) ₀ ⁻¹ A _(f) _(i)   [Equation 4]

In Equation 4, A_(fi) is a first matrix operation that converts atime-domain value corresponding to the ith sample data to angleinformation using a carrier frequency corresponding to ith sample dataof the frequency modulation model. A_(f0) ⁻¹ is an inverse matrix ofA_(f0), which is a second matrix operation that inversely converts angleinformation to a time-domain value using a reference frequency f₀. Thefirst matrix operation A_(fi) in Equation 4 may also be represented byEquations 5 and 6.

$\begin{matrix}{A_{f_{i}} = \left\lbrack {{\alpha_{f_{i}}\left( \theta_{1} \right)},\ldots \mspace{14mu},{\alpha_{f_{i}}\left( {\theta \; k} \right)},\ldots \mspace{14mu},{\alpha_{f_{i}}\left( \theta_{K} \right)}} \right\rbrack^{T}} & \left\lbrack {{Equation}\mspace{14mu} 5} \right\rbrack \\{{\alpha_{f_{i}}\left( \theta_{k} \right)} = \left\lbrack {1,e^{\frac{j\; 2\; \pi \; d}{\lambda_{f_{i}}}\sin \; \theta_{k}},\ldots \mspace{14mu},e^{\frac{j\; 2\; {\pi {({M - 1})}}d}{\lambda_{f_{i}}}\sin \; \theta_{k}}} \right\rbrack} & \left\lbrack {{Equation}\mspace{14mu} 6} \right\rbrack\end{matrix}$

In Equation 5, the first matrix operation A_(fi) may be represented by aset of vectors α_(fi)(θ_(k)), in which K is a natural number greaterthan or equal to 1 and k is a natural number greater than or equal to 1and less than or equal to K. In Equation 6, d is a distance between thereceiving antennas of the antenna array included in the radar sensor310. j is an imaginary unit. A_(fi) is a wavelength corresponding to thecarrier frequency of the ith sample data. θ_(k) is a kth angle inA_(fi), and α_(fi)(θ_(k)) is a vector corresponding to the angle θ_(k)in the carrier frequency corresponding to the ith time index of thefrequency modulation model. A_(fi) may be a K×M matrix consisting of Krows and M columns.

Here, A_(fi)Y(i), which indicates a result of matrix product calculationbetween the matrix A_(fi) of Equation 5 and Y(i) of Equation 2, may be aK×1 dimensional vector. In the result A_(fi)Y(i) of the matrix productcalculation, an element in a kth row may be a value corresponding to aprobability of Y(i) being the kth angle θ_(k) and may indicate angleinformation. Thus, based on a result of applying the first matrixoperation A_(fi) to the ith sample data Y(i), azimuth angle informationin the ith time index may be estimated.

According to an example, the processor 320 may change a detection areaor a detection resolution based on a result of measuring a 3D positionof an object as described above, and adjust a characteristic of atransmission signal based on a result of the changing. For example, whenit is detected that there is no object nearby, the processor 320 mayincrease an intensity of the transmission signal to expand the detectionarea. In addition, for more precise or closer detection, the processor320 may adjust a characteristic of a change in the carrier frequency ofthe transmission signal.

FIG. 4 is a diagram illustrating an example of a 3D position measuringapparatus.

Referring to FIG. 4, a 3D position measuring apparatus includes, forexample, a radar sensor 410 and a signal processor 450.

The radar sensor 410 may generate an FMCW signal based on a frequencymodulation control signal transferred from the signal processor 450, andmay transmit the generated FMCW signal as a transmission signal througha transmitting antenna 430. In addition, the radar sensor 410 mayobtain, through a receiving antenna 435, a received signal resultingfrom the FMCW signal being reflected by an object, and being incident onthe radar sensor 410. The transmitting antenna 430 may include aplurality of transmitting antennas, and the receiving antenna 435 mayinclude a plurality of receiving antennas.

The radar sensor 410 may include an FMCW signal generator 415, a poweramplifier 420, the transmitting antenna 430, the receiving antenna 435,a low-noise amplifier 440, and a frequency mixer 445.

The FMCW signal generator 415 may generate a FMCW signal 402 of which acarrier frequency varies over time based on setting information of atransmission signal. The setting information of the transmission signalmay include setting information associated with settings of a detectionarea or a detection resolution. In an example, the FMCW signal generator415 may include a voltage-controlled oscillator (VCO) circuit forgenerating various oscillation frequencies, and a phase-locked loop(PLL) circuit for improving stability of an output frequency of the VCOcircuit.

The FMCW signal generator 415 may generate the FMCW signal 402 bymodulating the carrier frequency based on a frequency modulation model401 defined by a processor 455. The FMCW signal 402 may also be referredto as a chirp signal. The frequency modulation model 401 may be a modelindicating a change in a carrier frequency of a transmission signal tobe transmitted through the radar sensor 410. In the frequency modulationmodel 401, a vertical axis indicates a magnitude of the carrierfrequency and a horizontal axis indicates a time. For example, thefrequency modulation model 401 may have a pattern in which the carrierfrequency changes linearly or nonlinearly over time.

In the example of FIG. 4, the frequency modulation model 401 may have apattern such that a carrier frequency varies linearly over time. TheFMCW signal generator 415 may generate the FMCW signal 402 having apattern such that the carrier frequency changes based on the frequencymodulation model 401. For example, as illustrated, the FMCW signal 402may correspond to a waveform in which the carrier frequency graduallyincreases in some time intervals, and gradually decreases in other timeintervals. In the graph illustrating the FMCW signal 402, a verticalaxis indicates a magnitude of the FMCW signal 402, and a horizontal axisindicates a time.

The FMCW signal 402 generated by the FMCW signal generator 415 may betransferred to the power amplifier 420. The power amplifier 420 mayamplify the received FMCW signal 402, and transfer the amplified FMCWsignal to the transmitting antenna 430. The transmitting antenna 430 mayradiate the amplified FMCW signal as the transmission signal.

The receiving antenna 435 may receive, as the received signal, areflected signal obtained from the radiated transmission signal beingreflected by an object and then returned. The low-noise amplifier 440may amplify and output only a received signal component excluding noisefrom the received signal. The frequency mixer 445 may demodulate aprevious signal, for example, the original chirp signal, which is onebefore the frequency modulation, from the received signal amplified bythe low-noise amplifier 440. The frequency mixer 445 may then transferthe demodulated signal to the signal processor 450.

The signal processor 450 may process the received signal transferredfrom the radar sensor 410 and estimate 3D position information of theobject. The signal processor 450 may include, for example, the processor455, a low-pass filter (LPF) 460, and an analog-to-digital converter(ADC) 465.

The LPF 460 may filter a low-frequency band signal out of the receivedsignal transferred from the radar sensor 410 to reduce noise of ahigh-frequency component that is included in the received signal. TheADC 465 may convert, to a digital signal, the received signal that is ananalog signal obtained through such low-pass filtering. The processor455 may output, to the FMCW signal generator 415, the frequencymodulation control signal for generating the FMCW signal 402, andestimate the 3D position information of the object based on a receivedsignal through a signal processing operation.

In the illustrated example, the processor 455 may compare a frequency408 of the reflected signal (or indicated by Rx) and a frequency 407 ofthe transmission signal (or indicated by Tx). The processor 455 maydetect a difference between the frequency 408 of the reflected signaland the frequency 407 of the transmission signal, and generate a beatfrequency signal indicating the difference between the frequency 408 andthe frequency 407. Such a frequency difference between the reflectedsignal and the transmission signal may indicate a difference f_(beat)during a time interval in which the carrier frequency increases overtime in the frequency modulation model 401 in a graph 409. The frequencydifference f_(beat) may be proportional to a distance between the radarsensor 410 and the object. Thus, the distance between the radar sensor410 and the object may be derived from the frequency difference betweenthe reflected signal and the transmission signal.

In an example, distance information with respect to a position of theobject may be calculated as represented by Equation 7.

$\begin{matrix}{R = \frac{c \times T_{chirp} \times f_{beat}}{2 \times B}} & \left\lbrack {{Equation}\mspace{14mu} 7} \right\rbrack\end{matrix}$

In Equation 7, R is a distance, or a range, between the radar sensor 410and the object, and c is a velocity of light. T_(chirp) is a time lengthcorresponding to an ascending interval in which the carrier frequencyincreases in the radiated transmission signal. B is a modulationfrequency bandwidth. A beat frequency f_(beat) is a frequency differencebetween the transmission signal and the reflected signal at a time pointin the ascending interval. The beat frequency f_(beat) may be derived asrepresented by Equation 8.

$\begin{matrix}{f_{beat} = \frac{t_{d} \times B}{T_{chirp}}} & \left\lbrack {{Equation}\mspace{14mu} 8} \right\rbrack\end{matrix}$

In Equation 8, f_(beat) is a beat frequency, and t_(d) is areciprocating delay time with respect to a position of the object, whichcorresponds to a time difference, or a delay time, between a time pointat which the transmission signal is radiated (or transmitted) and a timepoint at which the reflected signal is received. In addition, B is amodulation frequency bandwidth.

FIG. 5 is a diagram illustrating an example of an arrangement ofantennas of a radar sensor.

Referring to FIG. 5, an antenna array 500 of a radar sensor may includetransmitting antennas 510 and 520, and receiving antennas 530 and 540.The transmitting antennas 510 and 520 form a plurality of transmissionchannels, and the receiving antennas 530 and 540 form a plurality ofreception channels. In an example, the antenna array 500 may be providedin a form of series-fed patch, and the transmitting antennas 510 and 520and the receiving antennas 530 and 540 may be arranged in a horizontaldirection in the radar sensor, or arranged widthwise in the radarsensor. Based on a characteristic of such an arrangement of thetransmitting antennas 510 and 520, there may be a characteristicindicating a change of a center direction of a transmission signal basedon a change in a frequency band, which is described above with referenceto FIG. 2. However, there may be no such change in a horizontaldirection as the change of the center direction of the transmissionsignal based on the frequency band. In another example, the radar sensormay include an antenna that has a frequency scanning characteristic.

FIG. 6 is a diagram illustrating an example of a receiving antenna arrayof a radar sensor.

A 3D position measuring apparatus may estimate an azimuth with respectto a position of an object by analyzing reflected signals that areobtained through receiving antennas respectively forming a plurality ofreception channels. Referring to FIG. 6, reflected signals that arereceived respectively through reception channels may have a phasedifference from a reference phase. The reference phase may be anarbitrary phase or a phase of one of the reception channels.

The 3D position measuring apparatus may generate a radar vector of adimension corresponding to the number of the reception channels based onthe reflected signals received through the reception channels. Forexample, when a radar sensor has four reception channels, the 3Dposition measuring apparatus may generate a four-dimensional radarvector including a phase value corresponding to each of the receptionchannels. The phase value corresponding to each of the receptionchannels may be a numerical value indicating the phase differencedescribed in the foregoing.

For another example, when the radar sensor includes one transmissionchannel and four reception channels, a transmission signal radiatedthrough the transmission channel may be reflected from a position of anobject, and the reflected signal may be received respectively throughthe four reception channels. For example, as illustrated, a receivingantenna array 610 includes a first receiving antenna 611, a secondreceiving antenna 612, a third receiving antenna 613, and a fourthreceiving antenna 614. In the example of FIG. 6, a phase of a signal tobe received by the first receiving antenna 611 is set to be a referencephase. In the example, when a reflected signal 608 that is reflectedfrom a position of a same object is received by the receiving antennaarray 610, an additional distance Δ of a distance from the position ofthe object to the second receiving antenna 612, compared to a distancefrom the position of the object to the first receiving antenna 611, maybe represented by Equation 9.

Δ=d×sin(θ)  [Equation 9]

In Equation 9, θ is an angle of arrival (AOA) at which the reflectedsignal 608 is received from the position of the object, and d is adistance between the receiving antennas. c is a velocity of light in theair which is taken as a constant. Here, c=fλ, and thus a phase change Win the second receiving antenna 612 due to the additional distance 4 maybe represented by Equation 10.

$\begin{matrix}{W = {\frac{2\pi}{\lambda}d \times {\sin (\theta)}}} & \left\lbrack {{Equation}\mspace{14mu} 10} \right\rbrack\end{matrix}$

The phase change W may correspond to a phase difference between awaveform of a reflected signal received by the first receiving antenna611 and a waveform of a reflected signal received by the secondreceiving antenna 612. In Equation 10 above, a wavelength A may beinversely proportional to a frequency f of the reflected signal 608. Forexample, when a change in a carrier frequency by a frequency modulationmodel is small, the frequency f may be considered a single initialfrequency, for example, f₀, in the frequency modulation model. Thus,when the phase change W is determined based on the received reflectedsignal 608, the 3D position measuring apparatus may determine the AOA θand estimate the azimuth with respect to the position of the objectbased on the determined AOA θ.

FIG. 7 is a diagram illustrating an example of estimating distanceinformation and elevation angle information from a reflected signal.

Referring to FIG. 7, in a first graph 710, a solid line indicates arough waveform of a transmission signal 712 to be transmitted by atransmitting antenna, and a broken line indicates a rough waveform of areflected signal 714 to be received by a receiving antenna.

In the example of FIG. 7, the transmission signal 712 having a patternin which a carrier frequency increases linearly will be described forthe convenience of description. For example, the carrier frequency maylinearly increase by a frequency bandwidth BW from an initial frequencyf_(c) to a last frequency f_(c)+BW.

In the example, a distance to an object may be estimated based on a timedifference between the transmission signal 712 and the reflected signal714.

A 3D position measuring apparatus may calculate a beat frequencycorresponding to a frequency difference between the transmission signal712 and the reflected signal 714, and obtain a beat frequency signalindicating a change of the beat frequency over time. An example of thebeat frequency signal is as illustrated in a second graph 720. The beatfrequency may correspond to a reciprocating time or distance taken up toa time at which the transmission signal 712 is reflected by the objectto be the reflected signal 714 and the reflected signal 714 is received.The beat frequency may be used to estimate distance informationassociated with the distance to the object. In the example, the 3Dposition measuring apparatus may obtain a beat frequency signal 722corresponding to a chirp signal.

The 3D position measuring apparatus may sample the beat frequency signal722 corresponding to the chirp signal (corresponding to one period). The3D position measuring apparatus may then obtain groups of sample data byconverting a signal value obtained by sampling the beat frequency signal722 to a digital value. Here, a measurable beat frequency may bedetermined based on a sampling frequency that samples the beat frequencysignal 722, and this may be associated with a detection area, which is ameasurable distance.

In the example, all the groups of sample data that are sampled from thebeat frequency signal 722 include a first sample data group 732, asecond sample data group 734, a third sample data group 736, and afourth sample data group 738 that respectively correspond to differentfrequency bands. The first sample data group 732 is a group of sampledata 742 corresponding to a first frequency band, and the second samplegroup 734 is a group of sample data 744 corresponding to a secondfrequency band. In addition, the third sample data group 736 is a groupof sample data 746 corresponding to a third frequency band, and thefourth sample data group 738 is a group of sample data 748 correspondingto a fourth frequency band. The first through fourth frequency bands mayhave scopes respectively corresponding to four frequency bands intowhich the frequency band from the initial frequency f_(c) through thelast frequency f_(c)+BW that is described above is divided.

In this example, distance information with respect to a position of theobject may be derived from a result of applying a time-frequencyanalysis method to each of the sample data groups 732, 734, 736, and738. In addition, elevation angle information with respect to theposition of the object may be derived from a result of separating eachof the sample data groups 732, 734, 736, and 738 of the differentfrequency bands and applying the time-frequency analysis method tosample data included in each of the sample data groups 732, 734, 736,and 738. To estimate the elevation angle information, all or some of thesample data groups obtained by sampling the chirp signal may be used.

As described above, a transmission signal to be transmitted fromtransmitting antennas may be different in a center direction for eachfrequency band in a vertical direction in which the transmission signalproceeds. The 3D position measuring apparatus may separate the sampledata groups 732, 734, 736, and 738 of different frequency bands usingsuch a characteristic of the transmission signal, and perform thetime-frequency analysis method such as a Fourier transform or a WF toestimate elevation information in the vertical direction. In an example,the 3D position measuring apparatus may simultaneously derive thedistance information and the elevation angle information with respect toa position of the object through the time-frequency analysis method. Theelevation angle information in the vertical direction may be estimatedin a time domain, and the distance information may be estimated in afrequency domain.

Through such a processing method described above, the 3D positionmeasuring apparatus may effectively estimate a position of an object inan elevation angle direction without using an antenna of differentperformance or without applying a complex antenna arrangement. Thus, itis possible to measure a 3D position of the object only with relativelyless complex control and a simple antenna arrangement, and to reduce acost used for measuring the 3D position.

In an example, the 3D position measuring apparatus may estimate anazimuth with respect to a position of the object through DBF. Forexample, the 3D position measuring apparatus may calculate a differenceoccurring among reflected signals received respectively by receivingantennas, and estimate a direction in which a reflected signal isreceived based on the calculated difference. The 3D position measuringapparatus may estimate the azimuth of the object based on the estimateddirection.

FIGS. 8 and 9 are flowcharts illustrating an example of a 3D positionmeasuring method using a radar sensor.

Referring to FIG. 8, in operation 810, a 3D position measuring apparatustransmits, through a radar sensor, a transmission signal of which acarrier frequency varies over time. For example, the 3D positionmeasuring apparatus may generate a FMCW signal by modulating a carrierfrequency based on a frequency modulation model that uses a linearfrequency modulation method, and may radiate the generated FMCW signalthrough one or more transmitting antennas of the radar sensor. Inoperation 820, the 3D position measuring apparatus obtains, through theradar sensor, a reflected signal from the transmission signal beingreflected by an object. For example, the 3D position measuring apparatusmay receive the reflected signal through one or more receiving antennasof the radar sensor.

In operation 830, the 3D position measuring apparatus obtains a beatfrequency signal indicating a frequency difference between thetransmission signal and the reflected signal. For example, the 3Dposition measuring apparatus may calculate a beat frequency signal foreach of reception channels respectively corresponding to the receivingantennas. In operation 840, the 3D position measuring apparatusestimates 3D position information of the object based on the beatfrequency signal. For example, the 3D position measuring apparatus mayestimate the 3D position information of the object based on groups ofsample data of different frequency bands that are extracted from thebeat frequency signal. Hereinafter, operation 840 will be described ingreater detail with reference to FIG. 9.

Referring to FIG. 9, in operation 910, the 3D position measuringapparatus extracts groups of sample data from the beat frequency signal.For example, the 3D position measuring apparatus may extract the groupsof sample data by sampling the beat frequency signal at sampling points,and converting signal values of sampled beat frequency signals tocorresponding digital signal values. The 3D position measuring apparatusmay extract groups of sample data from a beat frequency signalcorresponding to a chirp signal.

In operation 920, the 3D position measuring apparatus estimates adistance and an elevation angle with respect to a position of the objectbased on groups of sample data of different frequency bands that areincluded in the extracted groups of sample data. For example, the 3Dposition measuring apparatus may estimate the elevation angle withrespect to the position of the object using a change of a centerdirection of the transmission signal for each frequency band of thetransmitting antennas included in the radar sensor. For example, the 3Dposition measuring apparatus may estimate the distance and the elevationangle with respect to the position of the object by applying atime-frequency analysis method to the groups of sample data of thedifferent frequency bands. The time-frequency analysis method mayinclude an STFT and a WT, for example. The 3D position measuringapparatus may calculate the distance and the elevation anglesimultaneously through the time-frequency analysis method. For a moredetailed description of operation 920 of estimating the distance and/orthe elevation angle, reference may be made to the description above withreference to FIGS. 4 and 7.

In operation 930, the 3D position measuring apparatus estimates anazimuth with respect to the position of the object based on beatfrequency signals respectively corresponding to the receiving antennasof the radar sensor. The 3D position measuring apparatus may estimatethe azimuth with respect to the position of the object using a DBFmethod, a MUSIC method, an ESPRIT, a MVDR method, or a Bartlett'smethod, for example. For example, the 3D position measuring apparatusmay estimate the azimuth through the DBF method that estimates adirection in which a reflected signal is received based on a differenceoccurring among the beat frequency signals. For a more detaileddescription of operation 930 of estimating the azimuth, reference may bemade to what has been described above with reference to FIGS. 3 and 6.

FIG. 10 is a diagram illustrating an example of a computing apparatus1000.

Referring to FIG. 10, the computing apparatus 1000 may be an apparatusthat may perform a function of measuring a 3D position of an object asdescribed above. In an example, the computing apparatus 1000 may performthe operations and functions of the 3D position measuring apparatus 300described above with reference to FIG. 3. The computing apparatus 1000may be used for automated or autonomous driving, driver assistance,facial recognition, gesture recognition, surveillance/security systems,and the like. The computing apparatus 1000 may operate as describedabove by being provided in an image processing apparatus, a smartphone,a wearable device, a tablet computer, a netbook, a laptop, a desktop, ahead-mounted display (HMD), a self-driving vehicle, or a smart vehicle,for example.

Referring to FIG. 10, the computing apparatus 1000 includes, forexample, a processor 1010, a storage 1020, a sensor 1030, an inputdevice 1040, an output device 1050, and a network device 1060. Theprocessor 1010, the storage 1020, the sensor 1030, the input device1040, the output device 1050, and the network device 1060 maycommunicate with one another through a communication bus 1070.

The processor 1010 may execute functions and instructions in thecomputing apparatus 1000. For example, the processor 1010 may processinstructions stored in the storage 1020. The processor 1010 may performone or more, or all, of operations described above with reference toFIGS. 1a through 9.

The storage 1020 may store information or data to be processed by theprocessor 1010. The storage 1020 may store instructions to be executedby the processor 1010. The storage 1020 may include a non-transitorycomputer-readable storage medium, for example, a random-access memory(RAM), a dynamic RAM (DRAM), a static RAM (SRAM), a magnetic hard disk,an optical disc, a flash memory, an electrically erasable programmableread-only memory (EPROM), a floppy disk, or other types of acomputer-readable storage medium that are well-known in the relatedtechnical field.

The sensor 1030 may include one or more sensors, for example, a radarsensor, an image sensor, and/or the like.

The input device 1040 may receive an input from a user through a tactileinput, a video input, an audio input, or a touch input. The input device1040 may include, for example, a keyboard, a mouse, a touchscreen, amicrophone, and/or other devices that may detect the input from the userand transmit the detected input.

The output device 1050 may provide an output of the computing apparatus1000 to a user through a visual, auditory, or tactile channel. Theoutput device 1050 may include, for example, a liquid crystal display(LCD), a light-emitting diode (LED) display, a touchscreen, a speaker, avibration generator, and/or other devices that may provide the user withthe output. In an example, the output device 1050 may provide a resultof estimating 3D position information of an object by the processor 1010using any one or any combination of any two or more of visualinformation, auditory information, or haptic information.

The network device 1060 may communicate with an external device througha wired or wireless network. For example, the network device 1060 maycommunicate with the external device through a wired communicationmethod, or a wireless communication method including, for example,Bluetooth, WiFi, third-generation (3G) communication, long-termevolution (LTE) communication, or the like.

The processors 320, 455, and 1010, the FMCW signal generator 415, thestorage 1020, the communication bus 1070, the processors, the memories,and other components and devices in FIGS. 1a to 10 that perform theoperations described in this application are implemented by hardwarecomponents configured to perform the operations described in thisapplication that are performed by the hardware components. Examples ofhardware components that may be used to perform the operations describedin this application where appropriate include controllers, sensors,generators, drivers, memories, comparators, arithmetic logic units,adders, subtractors, multipliers, dividers, integrators, and any otherelectronic components configured to perform the operations described inthis application. In other examples, one or more of the hardwarecomponents that perform the operations described in this application areimplemented by computing hardware, for example, by one or moreprocessors or computers. A processor or computer may be implemented byone or more processing elements, such as an array of logic gates, acontroller and an arithmetic logic unit, a digital signal processor, amicrocomputer, a programmable logic controller, a field-programmablegate array, a programmable logic array, a microprocessor, or any otherdevice or combination of devices that is configured to respond to andexecute instructions in a defined manner to achieve a desired result. Inone example, a processor or computer includes, or is connected to, oneor more memories storing instructions or software that are executed bythe processor or computer. Hardware components implemented by aprocessor or computer may execute instructions or software, such as anoperating system (OS) and one or more software applications that run onthe OS, to perform the operations described in this application. Thehardware components may also access, manipulate, process, create, andstore data in response to execution of the instructions or software. Forsimplicity, the singular term “processor” or “computer” may be used inthe description of the examples described in this application, but inother examples multiple processors or computers may be used, or aprocessor or computer may include multiple processing elements, ormultiple types of processing elements, or both. For example, a singlehardware component or two or more hardware components may be implementedby a single processor, or two or more processors, or a processor and acontroller. One or more hardware components may be implemented by one ormore processors, or a processor and a controller, and one or more otherhardware components may be implemented by one or more other processors,or another processor and another controller. One or more processors, ora processor and a controller, may implement a single hardware component,or two or more hardware components. A hardware component may have anyone or more of different processing configurations, examples of whichinclude a single processor, independent processors, parallel processors,single-instruction single-data (SISD) multiprocessing,single-instruction multiple-data (SIMD) multiprocessing,multiple-instruction single-data (MISD) multiprocessing, andmultiple-instruction multiple-data (MIMD) multiprocessing.

The methods illustrated in FIGS. 1a to 10 that perform the operationsdescribed in this application are performed by computing hardware, forexample, by one or more processors or computers, implemented asdescribed above executing instructions or software to perform theoperations described in this application that are performed by themethods. For example, a single operation or two or more operations maybe performed by a single processor, or two or more processors, or aprocessor and a controller. One or more operations may be performed byone or more processors, or a processor and a controller, and one or moreother operations may be performed by one or more other processors, oranother processor and another controller. One or more processors, or aprocessor and a controller, may perform a single operation, or two ormore operations.

Instructions or software to control computing hardware, for example, oneor more processors or computers, to implement the hardware componentsand perform the methods as described above may be written as computerprograms, code segments, instructions or any combination thereof, forindividually or collectively instructing or configuring the one or moreprocessors or computers to operate as a machine or special-purposecomputer to perform the operations that are performed by the hardwarecomponents and the methods as described above. In one example, theinstructions or software include machine code that is directly executedby the one or more processors or computers, such as machine codeproduced by a compiler. In another example, the instructions or softwareincludes higher-level code that is executed by the one or moreprocessors or computer using an interpreter. The instructions orsoftware may be written using any programming language based on theblock diagrams and the flow charts illustrated in the drawings and thecorresponding descriptions in the specification, which disclosealgorithms for performing the operations that are performed by thehardware components and the methods as described above.

The instructions or software to control computing hardware, for example,one or more processors or computers, to implement the hardwarecomponents and perform the methods as described above, and anyassociated data, data files, and data structures, may be recorded,stored, or fixed in or on one or more non-transitory computer-readablestorage media. Examples of a non-transitory computer-readable storagemedium include read-only memory (ROM), random-access memory (RAM), flashmemory, CD-ROMs, CD-Rs, CD+Rs, CD-RWs, CD+RWs, DVD-ROMs, DVD-Rs, DVD+Rs,DVD-RWs, DVD+RWs, DVD-RAMs, BD-ROMs, BD-Rs, BD-R LTHs, BD-REs, magnetictapes, floppy disks, magneto-optical data storage devices, optical datastorage devices, hard disks, solid-state disks, and any other devicethat is configured to store the instructions or software and anyassociated data, data files, and data structures in a non-transitorymanner and provide the instructions or software and any associated data,data files, and data structures to one or more processors or computersso that the one or more processors or computers can execute theinstructions. In one example, the instructions or software and anyassociated data, data files, and data structures are distributed overnetwork-coupled computer systems so that the instructions and softwareand any associated data, data files, and data structures are stored,accessed, and executed in a distributed fashion by the one or moreprocessors or computers.

While this disclosure includes specific examples, it will be apparentafter an understanding of the disclosure of this application thatvarious changes in form and details may be made in these exampleswithout departing from the spirit and scope of the claims and theirequivalents. The examples described herein are to be considered in adescriptive sense only, and not for purposes of limitation. Descriptionsof features or aspects in each example are to be considered as beingapplicable to similar features or aspects in other examples. Suitableresults may be achieved if the described techniques are performed in adifferent order, and/or if components in a described system,architecture, device, or circuit are combined in a different manner,and/or replaced or supplemented by other components or theirequivalents. Therefore, the scope of the disclosure is defined not bythe detailed description, but by the claims and their equivalents, andall variations within the scope of the claims and their equivalents areto be construed as being included in the disclosure.

What is claimed is:
 1. A method with three-dimensional (3D) positionmeasuring using a radio detection and ranging (radar) sensor,comprising: transmitting, through the radar sensor, a transmissionsignal of which a carrier frequency varies over time; obtaining, throughthe radar sensor, a reflected signal from the transmission signal beingreflected by an object; obtaining a beat frequency signal indicating afrequency difference between the transmission signal and the reflectedsignal; and estimating 3D position information of the object based ongroups of sample data of different frequency bands extracted from thebeat frequency signal.
 2. The method of claim 1, wherein the estimatingof the 3D position information of the object comprises: extracting aplurality of groups of sample data from the beat frequency signalcorresponding to a chirp signal, the plurality of groups of sample dataincluding the groups of sample data of the different frequency bands;and estimating a distance and an elevation angle with respect to aposition of the object based on the groups of sample data of thedifferent frequency bands.
 3. The method of claim 2, wherein theestimating of the distance and the elevation angle comprises: estimatingthe distance and the elevation angle with respect to the position of theobject by applying a time-frequency analysis method to the groups ofsample data of the different frequency bands.
 4. The method of claim 3,wherein the estimating of the distance and the elevation anglecomprises: calculating the distance and the elevation anglesimultaneously through the time-frequency analysis method.
 5. The methodof claim 3, wherein the time-frequency analysis method is a short-timeFourier transform (STFT) or a wavelet transform (WT).
 6. The method ofclaim 1, wherein the estimating of the 3D position information of theobject comprises: estimating an elevation angle with respect to aposition of the object using a change of a center direction of thetransmission signal for each frequency band among frequency bands oftransmitting antennas included in the radar sensor.
 7. The method ofclaim 6, wherein the transmitting antennas are arranged in a horizontaldirection in the radar sensor.
 8. The method of claim 1, wherein the 3Dposition information comprises a distance, an azimuth, and an elevationangle with respect to a position of the object.
 9. The method of claim8, wherein the estimating of the 3D position information of the objectcomprises: estimating the azimuth through digital beamforming forestimating a direction in which the reflected signal is received basedon a difference occurring among the beat frequency signals.
 10. Themethod of claim 1, wherein the estimating of the 3D position informationof the object comprises: estimating an azimuth with respect to aposition of the object based on beat frequency signals respectivelycorresponding to receiving antennas of the radar sensor.
 11. The methodof claim 1, wherein the carrier frequency is modulated based on afrequency modulation model that uses linear frequency modulation.
 12. Anon-transitory computer-readable storage medium storing instructionsthat, when executed by a processor, cause the processor to perform themethod of claim
 1. 13. An apparatus with three-dimensional (3D) positionmeasuring, comprising: a radio detection and ranging (radar) sensorconfigured to transmit a transmission signal of which a carrierfrequency varies over time, and obtain a reflected signal from thetransmission signal being reflected by an object; and a processorconfigured to obtain a beat frequency signal indicating a frequencydifference between the transmission signal and the reflected signal, andestimate 3D position information of the object based on groups of sampledata of different frequency bands extracted from the beat frequencysignal.
 14. The apparatus of claim 13, wherein the processor is furtherconfigured to: extract a plurality of groups of sample data from thebeat frequency signal corresponding to a chirp signal, the plurality ofgroups of sample data including the groups of sample data of thedifferent frequency bands; and estimate a distance and an elevationangle with respect to a position of the object based on the groups ofsample data of the different frequency bands.
 15. The apparatus of claim14, wherein the processor is further configured to: estimate thedistance and the elevation angle with respect to the position of theobject by applying a time-frequency analysis method to the groups ofsample data of the different frequency bands.
 16. The apparatus of claim15, wherein the time-frequency analysis method is a short-time Fouriertransform (STFT) or a wavelet transform (WT).
 17. The apparatus of claim13, wherein the processor is further configured to: estimate anelevation angle with respect to a position of the object using a changeof a center direction of the transmission signal for each frequency bandamong frequency bands of transmitting antennas included in the radarsensor.
 18. The apparatus of claim 13, wherein the processor is furtherconfigured to: estimate an azimuth with respect to a position of theobject based on beat frequency signals respectively corresponding toreceiving antennas of the radar sensor.
 19. The apparatus of claim 18,wherein the processor is further configured to: estimate the azimuththrough digital beamforming for estimating a direction in which thereflected signal is received based on a difference occurring among thebeat frequency signals.
 20. An apparatus with three-dimensional (3D)position measuring, comprising: a radio detection and ranging (radar)sensor configured to: transmit a transmission signal of which a carrierfrequency varies over time, using a plurality of transmission antennascorresponding to respective frequency bands of the transmission signal;and obtain a reflected signal from the transmission signal beingreflected by an object; and a processor configured to: obtain beatfrequency signals respectively corresponding to receiving antennas ofthe radar sensor and indicating a frequency difference between thetransmission signal and the reflected signal; and estimate 3D positioninformation of the object based on groups of sample data of differentfrequency bands extracted from the beat frequency signals.
 21. Theapparatus of claim 20, wherein the 3D position information includes adistance and an elevation of a position of the object relative to aposition of the apparatus.
 22. The apparatus of claim 20, wherein theprocessor is further configured to estimate the 3D position informationby estimating an elevation angle with respect to a position of theobject based on a change of a center direction of the transmissionsignal for each of the respective frequency bands of the transmissionsignal.
 23. The apparatus of claim 20, wherein the processor is furtherconfigured to estimate the 3D position information by estimating adistance and an elevation angle with respect to a position of the objectby applying a time-frequency analysis method to the groups of sampledata of the different frequency bands.